Permission-Aware Expert Detection in Enterprise Search Results
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Solution Overview
Problem
Existing search systems fail to effectively identify and display subject matter experts related to search results while ensuring data security by inadvertently showing unauthorized information.
Innovation Solution
A permissions-aware search and knowledge management system that identifies subject matter experts based on search result content, metadata, and user interactions, and displays user identifications only for authorized users, using a knowledge graph and machine learning to ensure secure and relevant results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the search system displays all available expert information along with search results, then the completeness of expert identification is improved, but data security deteriorates due to inadvertent display of unauthorized information
Solution Approach 1:
The system performs preliminary permission verification before displaying expert information. The access control list is checked in advance to determine which experts the user is authorized to see, and only those pre-authorized experts are included in the search results display, preventing unauthorized information from being shown
2Measurement precision
If the search system performs comprehensive expert detection across all documents, then the accuracy of expert identification is improved, but computational energy consumption increases
Solution Approach 1:
The system applies local quality by performing expert detection only on documents and experts relevant to the user's permission level. Instead of uniformly analyzing all documents in the system, the expert detection is localized to subsets of documents the user is authorized to access, reducing overall computational energy while maintaining accuracy for visible results
3Object-affected harmful factors
If the search system filters experts based on user permissions, then data security is improved, but the quantity of displayed expert information decreases
Solution Approach 1:
The access control list acts as an intermediary between the user and the expert information. It mediates the display by selectively permitting or blocking specific experts based on user permissions, thus ensuring data security while still providing the maximum possible quantity of expert information that the user is authorized to view
Data Source
AI summary
Methods and apparatuses for automatically identifying subject matter experts related to search results and displaying user identifications for the subject matter experts along with the search results are described. A search system may identify the subject matter experts based on the content of the search results, metadata associated with the search results, and various interactions including user-document interactions in which a user has created, edited, shared, or commented on a document. As the search system will only surface search results for which the user of the search system that submitted the search query has permission to access and the identification of the subject matter experts is determined based on the search results, the search system may prevent the inadvertent display of unauthorized information.